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Hi Ege, More than an issue , I have a question: After reading your paper and the documentation of pathfindR, I understand that you use as an input any OMICs data for which you can run a "differential expression/abundance" analysis . Is this correct ? Also, when using your OMICs data with the score_terms() function: is there any data normalization method that you recommend? Cheers, -Mathias |
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Hey Mathias, You understood correctly. More generally, any data containing genes and p values associated with these genes (two-class comparison, WGCNA gene importance significances etc.) can be used with pathfindR. For Hope this helps, |
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Hey Mathias,
You understood correctly. More generally, any data containing genes and p values associated with these genes (two-class comparison, WGCNA gene importance significances etc.) can be used with pathfindR.
For
score_terms()
, we do not have any specific recommendation for data normalization. As long as distributions by samples are roughly equivalent, the method should provide reliable results. You can read how aggregated term scoring is performed hereHope this helps,
Best,
-E